numpy.asanyarray
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numpy.asanyarray(a, dtype=None, order=None)[source] - 
Convert the input to an ndarray, but pass ndarray subclasses through.
- Parameters
 - 
- 
aarray_like - 
Input data, in any form that can be converted to an array. This includes scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists, and ndarrays.
 - 
dtypedata-type, optional - 
By default, the data-type is inferred from the input data.
 - 
order{‘C’, ‘F’}, optional - 
Whether to use row-major (C-style) or column-major (Fortran-style) memory representation. Defaults to ‘C’.
 
 - 
 - Returns
 - 
- 
outndarray or an ndarray subclass - 
Array interpretation of
a. Ifais an ndarray or a subclass of ndarray, it is returned as-is and no copy is performed. 
 - 
 
See also
- 
 
asarray - 
Similar function which always returns ndarrays.
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ascontiguousarray - 
Convert input to a contiguous array.
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asfarray - 
Convert input to a floating point ndarray.
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asfortranarray - 
Convert input to an ndarray with column-major memory order.
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asarray_chkfinite - 
Similar function which checks input for NaNs and Infs.
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fromiter - 
Create an array from an iterator.
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fromfunction - 
Construct an array by executing a function on grid positions.
 
Examples
Convert a list into an array:
>>> a = [1, 2] >>> np.asanyarray(a) array([1, 2])
Instances of
ndarraysubclasses are passed through as-is:>>> a = np.array([(1.0, 2), (3.0, 4)], dtype='f4,i4').view(np.recarray) >>> np.asanyarray(a) is a True
 
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    https://numpy.org/doc/1.18/reference/generated/numpy.asanyarray.html